Joined September 2025
Harbor Adapters and Harbor-Index (previously named as harbor-mix) accepted at NeurIPS E&D! Congrats and special thanks to all of our contributors, advisors, and funding partners!
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As nearly all AGI labs are using harbor format, we’re really honored and proud to build the bridge. Standardization is never easy, but helps the most.
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Introducing Harbor-Index, a compact, diverse, and high-quality benchmark built to challenge frontier agents. We carefully select, audit and fix 82 high-signal tasks out of 6,627 candidates spanning 54 benchmarks. No agent gets above 30%. (1/5)
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Every task is solidified through multiple iterations of audits and patches from LLM judges and human reviewers. As a result, we removed broken tasks so failures reflect genuine capability gaps. We also address known reward hacks: out of 1,476 runs, only 9 managed to cheat. (4/5)
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Harbor-Index is live. Browse all 82 tasks and 1,476 rollouts at harbor-index.org Huge thanks to our funding partners (@OpenAI @AnthropicAI @GoogleDeepMind @Alibaba_Qwen @deepseek_ai @Kimi_Moonshot, @Zai_org, @MiniMax_AI, @XiaomiMiMo, @LaudeInstitute, @2077AI, @UniPat_AI), sandbox providers (@daytonaio, @modal), and our 120 contributors and advisors from @terminalbench and @harborframework who brought Harbor-Index to life! And finally, our deepest thanks to the open benchmark community that made Harbor-Index possible: @alexgshaw, @ryan_marten, @ekellbuch, @longphan3110, @slimshetty_, @ori_press, @fchollet, @ludomitch, @froger_romain, @ChowdhuryNeil, Qixing Zhou, @jonmlaurent, Xiang Deng, @mialon_gregoire, @MinyangTian1, @Mike_A_Merrill, Zhun Wang, Bofei Gao, @xdotli, @fangyu_lei, @samuelp1002, @terryyuezhuo, @Shanda_Li_2000, @yeeelow233, @idavidrein, Rui Yang, @christinexye, @AndyLin2001, @jyangballin, @nielstron, @BenShi34, Ryan Wong, and so many more benchmark authors. Join us to build the next iteration of Harbor-Index on discord.com/invite/2Pe5uWGcV…!
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CAIS AgenticSE Workshop Keynote Talk: Harbor Adapters & Harbor Index 30min video here: youtu.be/tvAAKX2XVus?si=84L2… Happy to be invited as a keynote speaker and present our recent study on Harbor Adapters and agentic evaluation!
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Lin Shi retweeted
The Harbor registry is getting an upgrade. Now, anyone can publish to the registry to make their dataset available to every Harbor user:
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Terminal-Bench is a leading benchmark for agents. Unfortunately it’s hard: most small coding agents get very low scores on TB2, so training/system ablations look flat - you can't tell what's working. Announcing OpenThoughts-TBLite - 100 curated TB2-style tasks, difficulty-calibrated so even 8B models can make progress. It's designed to give researchers measurable signal during development, providing faster feedback for experimental iteration while closely tracking true TB2 performance🧵
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Lin Shi retweeted
A new Harbor benchmark comprised of tasks from @SnorkelAI @bespokelabsai and Terminal-Bench 2.0 rejects due to difficulty. Useful for hillclimbing TB tasks with small models.
Terminal-Bench is a leading benchmark for agents. Unfortunately it’s hard: most small coding agents get very low scores on TB2, so training/system ablations look flat - you can't tell what's working. Announcing OpenThoughts-TBLite - 100 curated TB2-style tasks, difficulty-calibrated so even 8B models can make progress. It's designed to give researchers measurable signal during development, providing faster feedback for experimental iteration while closely tracking true TB2 performance🧵
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Lin Shi retweeted
Come help us build Terminal-Bench 3.0! It will be an extremely high quality, difficult benchmark.
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